The diagnostic role of the systemic inflammation index in patients with immunological diseases: a systematic review and meta-analysis

The identification of novel, easily measurable biomarkers of inflammation might enhance the diagnosis and management of immunological diseases (IDs). We conducted a systematic review and meta-analysis to investigate an emerging biomarker derived from the full blood count, the systemic inflammation index (SII), in patients with IDs and healthy controls. We searched Scopus, PubMed, and Web of Science from inception to 12 December 2023 for relevant articles and evaluated the risk of bias and the certainty of evidence using the Joanna Briggs Checklist and the Grades of Recommendation, Assessment, Development, and Evaluation Working Group system, respectively. In 16 eligible studies, patients with IDs had a significantly higher SII when compared to controls (standard mean difference, SMD = 1.08, 95% CI 0.75 to 1.41, p < 0.001; I2 = 96.2%, p < 0.001; moderate certainty of evidence). The pooled area under the curve (AUC) for diagnostic accuracy was 0.85 (95% CI 0.82–0.88). In subgroup analysis, the effect size was significant across different types of ID, barring systemic lupus erythematosus (p = 0.20). In further analyses, the SII was significantly higher in ID patients with active disease vs. those in remission (SMD = 0.81, 95% CI 0.34–1.27, p < 0.001; I2 = 93.6%, p < 0.001; moderate certainty of evidence). The pooled AUC was 0.74 (95% CI 0.70–0.78). Our study suggests that the SII can effectively discriminate between subjects with and without IDs and between ID patients with and without active disease. Prospective studies are warranted to determine whether the SII can enhance the diagnosis of IDs in routine practice. (PROSPERO registration number: CRD42023493142). Supplementary Information The online version contains supplementary material available at 10.1007/s10238-024-01294-3.

The robust evidence of dysregulation of inflammatory pathways in IDs has led to the routine use of circulating biomarkers of inflammation, e.g., C-reactive protein (CRP), erythrocyte sedimentation rate (ESR), and ferritin, to diagnose the presence of specific IDs and/or a state of active disease vs. remission in clinical practice [9][10][11][12][13].However, their limited diagnostic accuracy in several types of IDs has stimulated a significant body of research to identify better biomarkers [9,[14][15][16].In this context, alterations in the count and ratios of specific blood cell types, e.g., neutrophils, platelets, and lymphocytes, have been studied to diagnose the presence of IDs and predict disease progression [17][18][19][20][21][22][23].Over the last decade, another hematological cell index, the systemic inflammation index [SII = (neutrophil count x platelet count)/lymphocyte count] has been investigated in patients with cancer [24,25], cardiovascular disease [26], liver disease [27], and, more recently, in patients with coronavirus disease 2019 (COVID-19) [28].Notably, in studies of COVID-19 the SII has shown a superior predictive capacity for adverse clinical outcomes when compared to other hematological indexes, e.g., the neutrophil-to-lymphocyte ratio [29].
Given the increasing interest in the potential clinical utility of the SII, we conducted a systematic review and metaanalysis of studies investigating this hematological index in patients with IDs and healthy controls and in ID patients with active disease and remission.We speculated that the presence of IDs was associated with significantly higher SII values vs. healthy controls and that the presence of active disease in patients with IDs was associated with higher SII values vs. patients in remission.We also investigated the presence of possible associations between the effect size of the between-group differences in SII values and several relevant demographic and clinical parameters, including specific IDs, ID duration, CRP, and ESR.
Two independent investigators screened each abstract and, if relevant, the full-text article according to the following inclusion criteria: (i) assessment of the SII, (ii) comparisons between patients with IDs and healthy controls (case-control design), (iii) age ≥ 18 years, (iv) English language, and (v) full-text available.The references of each article were hand searched for additional studies.
The following information was independently extracted from each article and transferred to an electronic spreadsheet for analysis: year of publication, first author, study design, study country, type of ID, disease duration, sample size, age, male to female ratio, markers of inflammation (erythrocyte sedimentation rate, ESR, and C-reactive protein, CRP), the area under the receiver operating characteristic curve (AUROC) with 95% confidence intervals (CIs), and diagnostic sensitivity and specificity for the presence of ID and active disease.
We assessed the risk of bias of each study using the items listed in the Joanna Briggs Institute Critical Appraisal Checklist for analytical cross-sectional studies [30].Studies addressing ≥ 75, ≥ 50 and < 75%, and < 50% of the checklist items were ranked as having a low, intermediate, or high risk of bias, respectively.The certainty of evidence was assessed using the Grades of Recommendation, Assessment, Development and Evaluation (GRADE) Working Group system which considers the study design (retrospective or prospective), the risk of bias, the presence of unexplained heterogeneity, the indirectness of evidence, the imprecision of the results, the effect size (small, SMD < 0.5, moderate, SMD 0.5-0.8, and large, SMD > 0.8) [31], and the probability of publication bias [32].We complied with the Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) 2020 statement (Supplementary Table 1 and 2) [33], and registered the study protocol in the International Prospective Register of Systematic Reviews (PROSPERO registration number: CRD42023493142).

Statistical analysis
Between-group differences in SII values were assessed by creating forest plots of standardized mean differences (SMDs) and 95% CIs.A p value < 0.05 was considered statistically significant.Appropriate methods were used to extrapolate the means and standard deviations from the medians and interquartile ranges or ranges [34].The heterogeneity of the SMD across different studies was assessed using the Q-statistic (significance level set at a p value < 0.10) and ranked as low (I 2 ≤ 25%), moderate (25% < I 2 < 75%), or high (I 2 ≥ 75%) [35,36].A randomeffect model based on the inverse-variance method was used in the presence of high heterogeneity.Sensitivity analysis was conducted to assess the stability of the results of the meta-analysis [37].
The presence of publication bias was assessed using the Begg's and Egger's tests and the "trim-and-fill" method [38][39][40].The midas command was used to assess the diagnostic performance of the SII for the presence of IDs and/or active disease by estimating the summary receiver operating characteristic (SROC) [41].True positive (TP), false positive (FP), false negative (FN), and true negative (TN) values were either directly extracted or calculated from individual articles.
Univariate meta-regression and subgroup analyses were conducted to investigate possible associations between the SMD and the year of publication, study design, study country, ID type and duration, sample size, age, male to female ratio, ESR, and CRP.All statistical analyses were performed using Stata 14 (Stata Corp., College Station, TX, USA).
The forest plot showed that the SII values were significantly higher in patients with IDs when compared with controls (SMD = 1.08, 95% CI 0.75 to 1.41, p < 0.001; I 2 = 96.2%,p < 0.001; Fig. 2).The pooled SMD values were stable in sensitivity analysis, ranging between 0.96 and 1.13 (Supplementary Fig. 1).The Begg's (p = 0.005), but not the Egger's (p = 0.11), test indicated the presence of publication bias.The use of the "trim-and-fill" method led to the identification of six missing studies to be added to the left side of the funnel plot to ensure symmetry (Fig. 3).The resulting effect size was attenuated yet still significant (SMD = 0.70, 95% CI 0.31 to 1.08, p < 0.001).
The overall level of certainty was upgraded to moderate (rating 3) after considering the low-moderate risk of bias in all studies (no change), the high but partly explainable heterogeneity (no change), the lack of indirectness (no change), the relatively large effect size (SMD = 1.08, upgrade one Fig. 4 Forest plot of studies investigating the systemic inflammation index (SII) in patients with immunological diseases (IDs) and healthy controls according to type of ID level) [31], and the presence of publication bias which was addressed with the "trim-and-fill" method (no change).
The overall level of certainty was upgraded to moderate (rating 3) after considering the low-moderate risk of bias in all studies (no change), the high but partly explainable heterogeneity (no change), the lack of indirectness (no change), the relatively large effect size (SMD = 0.81, upgrade one level) [31], and the absence of publication bias (no change).

Discussion
The significant differences in the SII between IDs patients and healthy controls and between IDs patients with active disease and remissions reported in this systematic review and meta-analysis suggests the potential clinical utility of the SII as a diagnostic biomarker of IDs.The capacity of the SII to discriminate between different groups was considered excellent for the presence of IDs (pooled AUC = 0.85) and acceptable for the presence of active disease (pooled AUC = 0.74) [58,59].Sensitivity analyses confirmed the Fig. 8 Forest plot of studies investigating the systemic inflammation index (SII) in patients with immunological diseases (IDs) with active disease and remission according to type of ID stability of the results of the meta-analysis.In meta-regression, the effect size was not significantly associated with several demographic and clinical characteristics, particularly ID duration and conventional biomarkers of inflammation (CRP and ESR).This suggests that the between-group differences in the SII a) are also present in the early phases of the disease and b) may provide clinical information that complements or enhances that provided by available biomarkers of inflammation.Interestingly, subgroup analysis identified differences in the effect size between different types of IDs for the presence of IDs but not for the presence of active disease in patients with IDs.
The SII was initially studied in patients with liver cancer [60], with subsequent investigations reporting significant associations with clinical outcomes in different types of cancer [25,[61][62][63], as well as in other disease states [26][27][28].Studies conducted in patients with atherosclerosis have also reported the potential prognostic superiority of the SII over conventional risk factors [64].Furthermore, in patients with COVID-19 the SII, but not other hematological indices such as the aggregate index of systemic inflammation, the neutrophil-to-lymphocyte ratio, the monocyte-to-lymphocyte ratio, the platelet-tolymphocyte ratio, and the systemic inflammation response index, was independently associated with adverse outcomes [29].The potential diagnostic superiority of the SII specifically in IDs is further supported by the results of studies investigating the diagnostic performance of the CRP and the ESR in primary care using datalink sources.
For example, a study identified a total of 160,000 patients from the Clinical Practice Research Datalink in the UK who had conventional inflammatory markers tested in 2014 [15,65].The primary outcome was defined as any autoimmune disease or cancer coded within one year, or infection coded within one month of the index date of inflammatory marker testing.In the final cohort of 136,691 patients (median age of 55.4 years, 62% female), the AUC for autoimmune conditions was 0.71 (95% CI 0.60-0.72)for the CRP and 0.71 (95% CI 0.69-0.72)for the ESR [15].These values are considerably lower than the pooled AUC values observed in our study for the diagnosis of IDs (0.85, 95% CI 0.82-0.88).Despite these promising findings, appropriately designed prospective studies are warranted to investigate the diagnostic and prognostic capacity of the SII, singly or in combination with other biomarkers of inflammation and/or clinical parameters, in patients with different types of ID.
Our study has several strengths, including the assessment of the SII in different types of IDs within the autoinflammatory-autoimmune continuum including autoinflammatory, mixed-pattern, and autoimmune diseases [1,7,8], the assessment of possible associations between the effect size and several study and patient characteristics, and a rigorous evaluation of the risk of bias and the certainty of evidence.Furthermore, sensitivity analysis ruled out the effect of individual studies on the overall effect size.Important limitations include the focus of the studies identified in our search on a restricted number of IDs (RA, AS, UC, gout, SLE, PsA, OA, uveitis, sarcoidosis, GPA, and IgG4-RD), and the lack of evidence from studies in specific geographical location, particularly Europe and North and South America.These issues require further study given the established evidence of differences in inflammatory response across different types of IDs and ethnic groups [66][67][68][69][70][71].
In conclusion, our systematic review and meta-analysis has shown the potential utility of the SII in diagnosing the presence of IDs and active disease.However, additional research is required to confirm these observations and determine whether this haematologically derived index can enhance the diagnostic capacity of current biomarkers and other clinical parameters in patients with different types of IDs and ethnicity.
(2024) 24:27 27 Page 12 of 14 Funding Open Access funding enabled and organized by CAUL and its Member Institutions.The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.

Fig. 5
Fig. 5 Summary receiving characteristics (SROC) curve with 95% confidence region and prediction region of the systemic inflammation index (SII) for the presence of immunological diseases (IDs)

Table 1
Studies investigating the systemic inflammation index in patients with immunological diseases and healthy controls AS ankylosing spondylitis, GPA granulomatosis polyangiitis, IgG4-RD IgG4-related disease, M/F male to female ratio, OA

Table 2
Assessment of the risk of bias using the Joanna Briggs Institute critical appraisal checklist

Table 3
Studies investigating the diagnostic accuracy of the systemic inflammation index for immunological diseasesAUC area under the curve, AS ankylosing spondylitis, CI confidence interval, GPA granulomatosis polyangiitis, IgG4-RD IgG4-related disease, NR not reported, P prospective, R retrospective, SLE systemic lupus erythematosus, UC ulcerative colitis

Table 5
Studies investigating the diagnostic accuracy of the systemic inflammation index for disease activityAS ankylosing spondylitis, AUC area under the curve, CI confidence interval, OA osteoarthritis, P prospective, PsA psoriatic arthritis, R retrospective, RA rheumatoid arthritis, SLE systemic lupus erythematosus, UC ulcerative colitis